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In den WarenkorbZustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Verlag: Nova Science Publishers Inc, 2009
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Nova Science Publishers Inc, 2009
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: Nova Science Publishers, Incorporated, 2012
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
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In den WarenkorbZustand: New.
Verlag: Nova Science Publishers Inc, 2012
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
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In den WarenkorbZustand: New. Num Pages: 228 pages, tables. BIC Classification: PB. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 266 x 185 x 21. Weight in Grams: 672. . 2012. First Edition. Hardcover. . . . . Books ship from the US and Ireland.
Verlag: Nova Science Publishers Inc, 2009
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
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In den WarenkorbGebunden. Zustand: New. Offers a comprehensive discussion and theoretical details of the Markov model applications. This book describes the application of the techniques to real life problems, and the computer programs for using the techniques.KlappentextrnrnDuring.
Verlag: Nova Science Publishers Inc Jul 2009, 2009
ISBN 10: 1604569778 ISBN 13: 9781604569773
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 117,38
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In den WarenkorbBuch. Zustand: Neu. Neuware - During the recent past, there has been a great deal of interest in solving problems of repeated measures data employing the Markov chain models. Most of the researchers and users of such techniques are only transition probabilities of various orders to show relationships among various states. However, in the recent past, there are attempts to include covariates in order to analyse the transition probabilities. Due to lack of a book on this topic, it is difficult for the researchers, students, and other users to have a thorough understanding in applying the methods based on sound knowledge. In addition, there is a lack of suitable software to handle repeated measures for Markov model applications. The main purpose of the book is to provide a theoretical base to the readers who will be willing to use these techniques for real life situations as well as for those who intend to continue advanced research in this field. This book provides a comprehensive discussion and theoretical details of the techniques in this field along with their estimation and test procedures, application of the techniques to real life problems, and the computer programs for using the techniques.